Create a .qmd file

Anatomy of a Quarto document

Use your preferred editor

Add a YAML header

---
key: value
---

Add a YAML header

---
title: "Your Document"
author: "Your name"
date: today
format: 
  html:
    code-fold: show
    embed-resources: true
execute: 
  warning: false
---

Render your document to HTML/PDF/DOCX

1. Render button in RStudio / Preview button in VS Code

Render your document to HTML/PDF/DOCX

2. System shell via quarto render

terminal

quarto render document.qmd # defaults to html
quarto render document.qmd --to pdf
quarto render document.qmd --to docx

library(quarto)
quarto_render("document.qmd") # defaults to html
quarto_render("document.qmd", output_format = "pdf")

Add plain text with Markdown formatting

### Add a heading in your document

This is a sentence with some **bold text**, *italic text*, 
`code`, and a [link](https://quarto.org/).

Add plain text with Markdown formatting

*italics* and **bold**

superscript^2^ / subscript~2~

~~strikethrough~~

`verbatim code`

Add plain text with Markdown formatting

# Header 1

## Header 2

### Header 3

#### Header 4

##### Header 5

###### Header 6

Add images

![Image caption](figs/quartologo.png){width='20%' fig-align='left'}

Add equations

Formula for population mean: 

$$
\mu = \frac{\sum x}{N} 
$$ 

Add R code chunks (and code outputs)

```{r}
#| label: fig-scatterplot
#| fig-cap: "Scatterplot of flipper and bill lengths"

library(palmerpenguins) # for data
library(tidyverse)      # for data wrangling and visualization
library(knitr)          # for tables

ggplot(data = penguins, 
       aes(x = flipper_length_mm, 
           y = bill_length_mm)) +
  geom_point(aes(color = species, 
                 shape = species)) 
```

Add R code chunks (and code outputs)

```{r}
#| output-location: column
#| label: fig-scatterplot
#| fig-cap: "Scatterplot of flipper and bill lengths"
#| warning: false

library(palmerpenguins) # for data
library(ggplot2)        # for data visualization

ggplot(data = penguins, 
       aes(x = flipper_length_mm, 
           y = bill_length_mm)) +
  geom_point(aes(color = species, 
                 shape = species))
```

Options for R code chunks: https://quarto.org/docs/reference/cells/cells-knitr.html

Add Python code chunks (and code outputs)

```{python}
#| output-location: column
#| label: fig-scatterplot-py
#| fig-cap: "Scatterplot of flipper and bill lengths in Python"

import numpy as np
import matplotlib.pyplot as plt
from palmerpenguins import load_penguins

penguins = load_penguins()

penguins['species_color'] = penguins['species']
penguins['species_color'].replace(['Adelie', 'Chinstrap', 'Gentoo'],
                        ['red', 'green', 'blue'], inplace=True)

penguins.plot.scatter(x='flipper_length_mm', 
                      y='bill_length_mm',
                      c='species_color')
```

Add Markdown table

| fruit  | price |
|--------|-------|
| apple  | 2.05  |
| pear   | 1.37  |
| orange | 3.09  |

: Fruit prices {.striped .hover}

Add R table

```{r}
#| output-location: column
#| label: tbl-stats
#| tbl-cap: "Summary statistics for flipper and bill lengths"

penguins %>%
  group_by(species) %>%
  summarise(
    `Mean bill length` = mean(bill_length_mm, na.rm = T),
    `Mean flipper length` = mean(flipper_length_mm, na.rm = T),
    `Correlation, r` = cor(flipper_length_mm, bill_length_mm, use = "complete")
    ) %>%
  kable(digits = c(2, 2, 2, 2, 2))
```

Add Python table

```{python}
#| output-location: column
#| label: tbl-py
#| tbl-cap: "First rows of penguins dataframe"

from tabulate import tabulate
from IPython.display import Markdown

# Convert to markdown table
Markdown(tabulate(penguins[["species", "island", "bill_length_mm", "flipper_length_mm"]].head(), headers='keys', tablefmt='github'))
```

Add inline R or Python code

The palmerpenguins package contains data for ` {r} nrow(penguins) ` penguins.
Remove the space before {r} to make sure the code is evaluated!

The palmerpenguins package contains data for 344 penguins.

The palmerpenguins package contains data for `{python} penguins.shape[0]` penguins.

Add cross-references

![The Quarto logo](figs/quartologo.png){#fig-quarto width='20%' fig-align='left'}

See @fig-quarto for the Quarto logo.

See Figure 3 for the Quarto logo.

Add citations

• Add citation in text: @… (manually or using visual editor > Insert citation)

The palmerpenguins package was developed by @horst2020. We will create a document using Quarto [@quarto] and R [@R] or Python [@Python].

bibliography: references.bib

Add tabsets

::: {.panel-tabset}

## Element 1

## Element 2

:::

Add tabsets

Add footnotes

This sentence ends with a footnote.[^1]

[^1]: This is an example footnote.

Bonus features

• interactive outputs (only for HTML outputs):

  • htmlwidgets for R

  • Jupyter widgets for Python/Julia

  • Observable JS

  • Shiny for R and Python

• callouts

• videos

• diagrams

Bonus features

• code annotation

• article layout

• Extensions:

  • shortcodes and filters (e.g., fontawesome icons )
  • journal article formats
  • custom formats

• and much more! https://quarto.org/docs/guide/

Observable JS

viewof temp = Inputs.range([0, 100], {step: 1, value: 34, label: htl.html`Temp ℃`})

Converting temperature from ℃ to ℉

Celsius = ℃ and Fahrenheit = ℉.

```{ojs}
viewof temp = Inputs.range([0, 100], {step: 1, value: 34, label: htl.html`Temp ℃`})
```

Converting temperature from &#x2103; to &#x2109; <br>  
Celsius = ${d3.format(".0f")(temp)}&#x2103; and Fahrenheit = ${d3.format(".1f")(temp * 9/5 + 32)}&#x2109;.

Other output formats

Examples of advanced use cases

Awesome Quarto resources (only a selection!)

Bonus: What to do with my existing .Rmd or .ipynb?

For some of you - nothing changes! Keep using RMarkdown and Jupyter.

terminal

quarto render my-favorite.rmd --to html

terminal

quarto render my-favorite.ipynb --to html --execute

Bonus: Why Quarto, instead of RMarkdown

• Batteries included, shared syntax
• Choose your own editor and your preferred data science language
• Better accessibility and richer features out of the box
• More enhancements overtime - RMarkdown still maintained, but majority of new features built into Quarto

Quarto, crafted with love and care

Development of Quarto is sponsored by RStudio, PBC. The same core team works on both Quarto and R Markdown:

• Carlos Scheidegger (@cscheid)

• Charles Teague (@dragonstyle)

• Christophe Dervieux (@cderv)

• J.J. Allaire (@jjallaire)

• Yihui Xie (@yihui)

Here is the full contributors list. Quarto is open source and they welcome contributions in their github repository as well! https://github.com/quarto-dev/quarto-cli.

Attributions

The slides and materials for this workshop were heavily based on other existing guides and workshops:

• Quarto official documentation

• Getting Started with Quarto by Tom Mock (CC BY 4.0)

• Quarto workshop by Julien Barnier and Aurélie Siberchicot

Icon attributions:

• to do by Michael Appleford from Noun Project (CC BY 3.0)

Thank you very much for providing these open resources!

Feedback, further questions or want to connect?